US-12625152-B2 - Automated sample analyzer

US12625152B2US 12625152 B2US12625152 B2US 12625152B2US-12625152-B2

Abstract

A system includes a sample analyzing device reading measurements associated with a liquid sample; a display device displaying a graphical user interface (GUI) to a current user of the automated sample analyzer; processing circuitry; and a memory storing: a receiving engine which receives the measurements associated with the liquid sample from the sample analyzing device and storing the received measurements in memory; a configuration control engine which sets a configuration of a user model to correspond to the current user of the automated sample analyzer; a learning engine which detects and collect at least one pattern of interaction of the current user with the GUI; and a user interface engine which configures the GUI according to user-dependent configuration data of the configuration of the user model corresponding to the current user.

Inventors

Atsushi Matsushita
Kevin L. Nowak
Takayuki Mizutani
Aaron P. O'Reilly

Assignees

BECKMAN COULTER, INC.

Dates

Publication Date: 20260512
Application Date: 20211222

Claims (20)

1 . A system comprising: processing circuitry; and a memory storing: a learning engine which, when executed by the processing circuitry, causes the processing circuitry to: identify an accessing user of an automated sample analyzer and, upon validation, establish the accessing user as a current user; monitor interactions between the current user and the automated sample analyzer to generate interaction data; determine, based on interaction data, at least one pattern of interaction between the current user and the automated sample analyzer; determine, based on the at least one pattern of interaction, configuration data for the current user, the configuration data indicating at least one of an appearance of a graphical user interface displayed by the automated sample analyzer or a sequence of graphical user interfaces displayed by the automated sample analyzer; store the configuration data in a data repository in association with a user profile of the current user; a configuration control engine which, when executed by the processing circuitry, causes the processing circuitry to access the configuration data stored by a user data repository; and a user interface engine which, when executed by the processing circuitry, causes the processing circuitry to configure one or more graphical user interfaces for display by the automated sample analyzer according to the configuration data.
2 . The system of claim 1 , wherein the configuration control engine, when executed by the processing circuitry, causes the processing circuitry to: identify the accessing user and, upon validation, establish the accessing user as the current user; determine, based on a current time and the at least one pattern of interaction, a pattern of interaction for the current time; and cause display, within a graphical user interface of the automated sample analyzer, a shortcut to implement the pattern of interaction for the current time.
3 . The system of claim 1 , wherein the configuration data includes menu optimization data that defines a menu optimization comprising a set of menus for presentation within one or more graphical user interfaces or a set of menu items for presentation within the set of menus of the one or more graphical user interfaces.
4 . The system of claim 3 , wherein the menu optimization data is derived by artificial intelligence menu usage review of prior menu usage of the current user.
5 . The system of claim 4 , wherein an artificial intelligence engine analyzes a prior menu usage frequency of the current user to generate the configuration data.
6 . The system of claim 1 , wherein the configuration data is updated in the user data repository and comprises different graphical user interface configurations for different times with at least a first graphical user interface configuration for a first time range and a second graphical user interface configuration for a second time range.
7 . The system of claim 6 , wherein the different graphical user interface configurations for different times are determined based on interaction between the current user and one or more graphical user interfaces displayed by the automated sample analyzer within a predetermined time range.
8 . The system of claim 1 , wherein the learning engine includes an artificial neural network and the artificial neural network establishes a correlation between the at least one pattern of interaction with the current user, a history of interaction with the current user, and a configuration of the automated sample analyzer.
9 . The system of claim 1 , wherein the learning engine predicts a next action by image recognition.
10 . The system of claim 1 , wherein the learning engine shows previous actions of the current user in a diagram displayed in a graphical user interface, the graphical user interface providing an interface for user selection of one or more of the previous actions for demonstration in the diagram.
11 . A method comprising: identifying, by processing circuitry, an accessing user of an automated sample analyzer and, upon validation, establish the accessing user as a current user; monitoring, by the processing circuitry, interactions between the current user and the automated sample analyzer to generate interaction data; determining, by the processing circuitry and based on the interaction data, at least one pattern of interaction between the current user and the automated sample analyzer; determining, by the processing circuitry and based on the at least one pattern of interaction, configuration data for the current user, the configuration data indicating at least one of an appearance of a graphical user interface displayed by the automated sample analyzer or a sequence of graphical user interfaces displayed by the automated sample analyzer; storing, by the processing circuitry, the configuration data in a user data repository in association with a user profile of the current user; accessing, by the processing circuitry, the configuration data stored in the user data repository; and configuring, by the processing circuitry, one or more graphical user interfaces for display by the automated sample analyzer according to the configuration data.
12 . The method of claim 11 comprising: receiving, from a camera of the automated sample analyzer, image data representing a consumable for placement into the automated sample analyzer; classifying, using the processing circuitry, the consumable into a class of consumables based on the image data; and transmitting, using the processing circuitry, a control signal to physically adjust a sample input device of the automated sample analyzer to receive the consumable, the control signal corresponding to the class of consumables.
13 . The method of claim 12 , further comprising: transmitting, to a display device of the automated sample analyzer, a display signal for displaying a visual representation of the class of consumables or a portion of the image data.
14 . An automated sample analyzer comprising: a sample input device receiving a liquid sample; a sample analyzing device reading measurements associated with the liquid sample; a display device displaying a graphical user interface (GUI) to a current user of the automated sample analyzer, the GUI being for controlling or maintaining the automated sample analyzer by the current user; processing circuitry; and a memory storing: a receiving engine which, when executed by the processing circuitry, receives the measurements associated with the liquid sample from the sample analyzing device and stores the measurements in memory; a configuration control engine which, when executed by the processing circuitry, causes the processing circuitry to set a configuration of a user model to correspond to the current user of the automated sample analyzer; a learning engine which, when executed by the processing circuitry, causes the processing circuitry to detect and collect at least one pattern of interaction of the current user with the GUI; and a user interface engine which, when executed by the processing circuitry, causes the processing circuitry to configure the GUI according to user-dependent configuration data of the configuration of the user model corresponding to the current user, the user-dependent configuration data being received from a user data repository; wherein the learning engine, when executed by the processing circuitry, causes the processing circuitry to: identify an accessing user and, upon validation, establish the accessing user as the current user; monitor interaction between the current user and the GUI and store interaction data of the current user in association with time; determine, based on the interaction data, at least one time-cyclical pattern of interaction between the current user and the GUI; and store the at least one time-cyclical pattern of interaction.
15 . The automated sample analyzer of claim 14 , wherein the user-dependent configuration data includes menu optimization data that defines a menu optimization comprising a set of menus for presentation within the GUI or a set of menu items for presentation within the set of menus of the GUI; and the user interface engine, when executed by the processing circuitry; causes the processing circuitry to: display an optimized version of a menu; receive, via the GUI, a request to revert to a prior version of the menu; and responsive to the request, display the prior version of the menu.
16 . The automated sample analyzer of claim 14 , wherein the learning engine compares a current validation input and a prior validation input and, upon the current validation input being authenticated, automatically calibrates validation criteria with the current validation input.
17 . The automated sample analyzer of claim 14 , wherein the configuration control engine, provides to the current user, via the GUI, a representation of a short-cut of sequential actions to an end action.
18 . The automated sample analyzer of claim 14 , wherein the configuration control engine, provides to the current user, via the GUI, a representation of a shortened workflow, the shortened workflow being selected based on an experience level of the current user identified by the learning engine.
19 . The automated sample analyzer of claim 14 , wherein the configuration control engine, provides, via the GUI, a representation of a shortened workflow, the shortened workflow being selected based on at least one previous menu item selection of the current user identified by the learning engine.
20 . The automated sample analyzer of claim 14 , wherein the learning engine provides an output representing changes made to the user model and requests feedback, via the GUI, from the current user on the changes made to the user model.

Description

PRIORITY CLAIM AND CROSS-REFERENCE TO RELATED APPLICATION This application is a U.S. national stage filing under 35 U.S.C. § 371 from International Application No. PCT/US2021/064952, filed on Dec. 22, 2021, and published as WO 2022/146842 on Jul. 7 2022, which claims priority to U.S. Provisional Application Ser. No. 63/131,458 filed Dec. 29, 2020, the benefit of priority of each of which is claimed herein, and which applications and publication are hereby incorporated by reference herein in its their entirety. TECHNICAL FIELD Implementations pertain to an automated sample analyzer for analyzing liquid samples. BACKGROUND Automated sample analyzers for analyzing liquid samples are, oftentimes, used by many different people (e.g., scientific researchers, lab technicians, repair persons, and the like) with different use cases. However, the automated sample analyzer may provide the same user interface for each and every user. BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 illustrates the training and use of a machine-learning program, in accordance with some implementations. FIG. 2 illustrates an example neural network, in accordance with some implementations. FIG. 3 illustrates the training of an image recognition machine learning program, in accordance with some implementations. FIG. 4 illustrates the feature-extraction process and classifier training, in accordance with some implementations. FIG. 5 is a block diagram of a computing machine, in accordance with some implementations. FIG. 6 is a block diagram of an automated sample analyzer, in accordance with some implementations. FIG. 7 is a flow chart illustrating an example method for updating a user data repository, in accordance with some implementations. FIG. 8 is a flow chart illustrating an example method for identifying and storing a pattern of interaction, in accordance with some implementations. FIG. 9 illustrates an example menu, in accordance with some implementations. FIG. 10 illustrates an example collapsed menu hierarchy, in accordance with some implementations. FIGS. 11A-11C illustrate example display data associated with an automated sample analyzer, in accordance with some implementations. FIG. 12 is a block diagram of an example automated sample analyzer for analyzing a specimen, in accordance with some implementations. FIG. 13 illustrates an example automated sample analyzer, in accordance with some implementations. FIG. 14 illustrates an example system to configure automated sample analyzers based on configuration data derived from patterns of interaction by users of the automated sample analyzers, in accordance with some implementations. SUMMARY The following description and the drawings sufficiently illustrate specific implementations to enable those skilled in the art to practice them. Other implementations may incorporate structural, logical, electrical, process, and other changes. Portions and features of some implementations may be included in, or substituted for, those of other implementations. Implementations set forth in the claims encompass all available equivalents of those claims. According to some implementations, a system can include an automated sample analyzer that comprises: a sample input device receiving a liquid sample, a sample analyzing device reading measurements associated with the liquid sample, a display device displaying a graphical user interface (GUI) to a current user of the automated sample analyzer, the GUI being for controlling or maintaining the automated sample analyzer by the current user, processing circuitry, and a memory. The memory stores a receiving engine receiving the measurements associated with the liquid sample from the sample analyzing device and storing the received measurements in memory. The memory stores a configuration control engine which, when executed by the processing circuitry, causes the processing circuitry to set a configuration of a user model to correspond to the current user of the automated sample analyzer. The memory stores a learning engine which, when executed by the processing circuitry, causes the processing circuitry to detect and collect at least one pattern of interaction of the current user with the GUI. The memory stores a user interface engine which, when executed by the processing circuitry, causes the processing circuitry to configure the GUI according to user-dependent configuration data of the configuration of the user model corresponding to the current user, the user-dependent configuration data being received from a user data repository. Some implementations include a machine-readable medium storing all or a portion of the data and instructions stored in the memory. Some implementations include a method for performing all or a portion of the techniques described above. Some implementations include an apparatus comprising means for performing all or a portion of the techniques described above. DETAILED DESCRIPTION The following description and the drawings sufficien